title: The choice of reference gene affects statistical efficiency in quantitative PCR data analysis.
abstract: Quantitative polymerase chain reaction (qPCR), a highly sensitive method of measuring gene expression, is widely used in biomedical research. To produce reliable results, it is essential to use stably expressed reference genes (RGs) for data normalization so that sample-to-sample variation can be controlled. In this study, we examine the effect of different RGs on statistical efficiency by analyzing a qPCR data set that contains 12 target genes and 3 RGs. Our results show that choosing the most stably expressed RG for data normalization does not guarantee reduced variance or improved statistical efficiency. We also provide a formula for determining when data normalization will improve statistical efficiency and hence increase the power of statistical tests in data analysis.
authors.affiliation: Department of Health Outcomes and Policy, College of Medicine, University of Florida, Gainesville, FL.
authors.forename: Yi
authors.initials: Y
authors.lastname: Guo
authors.forename: Michael L
authors.initials: ML
authors.lastname: Pennell
authors.forename: Dennis K
authors.initials: DK
authors.lastname: Pearl
authors.forename: Thomas J
authors.initials: TJ
authors.lastname: Knobloch
authors.forename: Soledad
authors.initials: S
authors.lastname: Fernandez
authors.forename: Christopher M
authors.initials: CM
authors.lastname: Weghorst
mesh_terms: D015870:Gene Expression; D016133:Polymerase Chain Reaction / Q000379:methods*; D012015:Reference Standards